The values of college students in business simulation game: A means-end chain approach

Business simulation games (BSGs) enable students to practice making decisions in a virtual environment, accumulate experience in application of strategies, and train themselves in modes of decision-making. This study examines the value sought by players of BSG. In this study, a means-end chain (MEC) model was adopted as the basis, and ladder method soft laddering was used to conduct in-depth interviews with students who had experience in using BSGs. The chain concept of “attribute-consequence-value” was used to understand students’ value cognition structures. Content analysis was used to analyze the attributes-consequences-values for BSGs players, then converted into a Hierarchical Value Map (HVM). The results showed that students consider teamwork and market diversity as the most important attributes, and the consequences of a cooperative approach and market diversity are emotional exchange and multi-thinking, with the ultimate value brought to users by exchanges between teams and constant thinking being interpersonal relationships and a sense of accomplishment.     

hsmm — An R package for analyzing hidden semi-Markov models

Hidden semi-Markov models are a generalization of the well-known hidden Markov model. They allow for a greater flexibility of sojourn time distributions, which implicitly follow a geometric distribution in the case of a hidden Markov chain. The aim of this paper is to describe hsmm, a new software package for the statistical computing environment R. This package allows for the simulation and maximum likelihood estimation of hidden semi-Markov models. The implemented Expectation Maximization algorithm assumes that the time spent in the last visited state is subject to right-censoring. It is therefore not subject to the common limitation that the last visited state terminates at the last observation. Additionally, hsmm permits the user to make inferences about the underlying state sequence via the Viterbi algorithm and smoothing probabilities.     

HSP: A solution against heap sprays

Heap sprays are a new buffer overflow attack (BOA) form that can significantly increase the successful chance of a BOA even though the attacked process is protected by a lot of state-of-the-art anti-BOA mechanisms, such as ASLR, non-executable stack/DEP, signature-based IDSes, and type-safe languages. In this paper, we propose a glibc-and-ASLR-based solution to heap sprays—Heap Spray Protector (HSP). HSP controls the number and location of int 80 instructions in a process and hides the whereabouts of the only legal int 80 instruction; hence, HSP makes it difficult for attackers to issue a system call, let alone a heap spray attack. Moreover HSP can help ASLR defend against memory information leaking attacks. Furthermore, because HSP only modifies the glibc library and the kernel, it does not need to modify any source code or executable file. Finally, HSP allows attackers to execute as much code as possible before an attack can really create some damage; therefore, it enables the attacked hosts to collect more information about attackers which may be useful to block future attacks. Experimental results show HSP implemented on a Linux platform can effectively defend a system against heap sprays with less than 4.56% performance overhead.     

A dual K-Na selective Prussian blue nanotubes sensor

A strategy for dual sensing of Na⁺ and K⁺ ions using Prussian blue nanotubes via selective inter/deintercalation of K⁺ ion and competitive inhibition by Na⁺ ion, is reported. The analytical signal is derived from the cyclic voltammetry cathodic peak position E_pc of Prussian blue nanotubes. Na⁺ and K⁺ levels in a sample solution can be determined conveniently using one Prussian blue nanotubes sensor. In addition, this versatile method can be applied for the analysis of single type of either Na⁺ or K⁺ ions. The dual-ion sensor response towards Na⁺ and K⁺ can be described using a model based on the competitive inhibition effects of Na⁺ on K⁺ inter/deintercalation in Prussian blue nanotubes. Successful application of the Prussian blue nanotubes sensor for Na⁺ and K⁺ determination is demonstrated in artificial saliva.     

A study on effectiveness of extreme learning machine

Extreme learning machine (ELM), proposed by Huang et al., has been shown a promising learning algorithm for single-hidden layer feedforward neural networks (SLFNs). Nevertheless, because of the random choice of input weights and biases, the ELM algorithm sometimes makes the hidden layer output matrix H of SLFN not full column rank, which lowers the effectiveness of ELM. This paper discusses the effectiveness of ELM and proposes an improved algorithm called EELM that makes a proper selection of the input weights and bias before calculating the output weights, which ensures the full column rank of H in theory. This improves to some extend the learning rate (testing accuracy, prediction accuracy, learning time) and the robustness property of the networks. The experimental results based on both the benchmark function approximation and real-world problems including classification and regression applications show the good performances of EELM.     

The complexity of achievement and maintenance problems in agent-based systems

We completely classify the computational complexity of the basic achievement and maintenance agent design problems in bounded environments when these problems are parameterized by the number of environment states and the number of agent actions. The different problems are P-complete, NP-complete, co-NP-complete or PSPACE-complete (when they are not trivial). We also consider alternative achievement and maintenance agent design problems by allowing longer runs in environments (that is, our environments are bounded but the bounds are more liberal than was the case previously). Again, we obtain a complete classification but so that the different problems are DEXPTIME-complete, NEXPTIME-complete, co-NEXPTIME-complete or NEXPSPACE-complete (when they are not trivial).     

HiggsBounds: Confronting arbitrary Higgs sectors with exclusion bounds from LEP and the Tevatron

HiggsBounds is a computer code that tests theoretical predictions of models with arbitrary Higgs sectors against the exclusion bounds obtained from the Higgs searches at LEP and the Tevatron. The included experimental information comprises exclusion bounds at 95% C.L. on topological cross sections. In order to determine which search topology has the highest exclusion power, the program also includes, for each topology, information from the experiments on the expected exclusion bound, which would have been observed in case of a pure background distribution. Using the predictions of the desired model provided by the user as input, HiggsBounds determines the most sensitive channel and tests whether the considered parameter point is excluded at the 95% C.L. HiggsBounds is available as a Fortran 77 and Fortran 90 code. The code can be invoked as a command line version, a subroutine version and an online version. Examples of exclusion bounds obtained with HiggsBounds are discussed for the Standard Model, for a model with a fourth generation of quarks and leptons and for the Minimal Supersymmetric Standard Model with and without CP-violation. The experimental information on the exclusion bounds currently implemented in HiggsBounds will be updated as new results from the Higgs searches become available.

Program summary

Program title: HiggsBoundsCatalogue identifier: AEFF_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFF_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 55 733No. of bytes in distributed program, including test data, etc.: 1 986 213Distribution format: tar.gzProgramming language: Fortran 77, Fortran 90 (two code versions are offered).Computer: HiggsBounds can be built with any compatible Fortran 77 or Fortran 90 compiler. The program has been tested on x86 CPUs running under Linux (Ubuntu 8.04) and with the following compilers: The Portland Group Inc. Fortran compilers (pgf77, pgf90), the GNU project Fortran compilers (g77, gfortran).Operating system: LinuxRAM: minimum of about 6000 kbytes (dependent on the code version)Classification: 11.1External routines: HiggsBounds requires no external routines/libraries. Some sample programs in the distribution require the programs FeynHiggs 2.6.x or CPsuperH2 to be installed (see “Subprograms used”).Subprograms used:

Cat Id	Title	Reference
ADKT_v2_0	FeynHiggsv2.6.5	CPC 180(2009)1426
ADSR_v2_0	CPsuperH2.0	CPC 180(2009)312

Full-size table

     

Four-arc approximation to ellipses: The best in general

So far, the four-arc approximations to an ellipse E are made under the condition that the major and minor axes keep strictly unchanged. In general, however, this condition is unnecessary. Then the fitting can be further improved. Considering a representative quadrant of E, we first draw two auxiliary circular arcs tangent to E at the axes but having a gap ε at their boundary, such that the small arc S lies outside the large arc L. Meanwhile the extreme errors of S and L w.r.t. E are ε and −ε respectively. Giving the radii of S and L a decrement −ε/2 and an increment ε/2 brings them to join smoothly. Thus, reducing the overall error to minimum, an analytic solution in implicit form is derived.     

Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources

In this paper we continue previous studies on the computational efficiency of spiking neural P systems, under the assumption that some pre-computed resources of exponential size are given in advance. Specifically, we give a deterministic solution for each of two well known PSPACE-complete problems: QSAT and Q3SAT. In the case of QSAT, the answer to any instance of the problem is computed in a time which is linear with respect to both the number n of Boolean variables and the number m of clauses that compose the instance. As for Q3SAT, the answer is computed in a time which is at most cubic in the number n of Boolean variables.     

Generalized linear models with clustered data: Fixed and random effects models

The statistical analysis of mixed effects models for binary and count data is investigated. In the statistical computing environment R, there are a few packages that estimate models of this kind. The package lme4 is a de facto standard for mixed effects models. The package glmmML allows non-normal distributions in the specification of random intercepts. It also allows for the estimation of a fixed effects model, assuming that all cluster intercepts are distinct fixed parameters; moreover, a bootstrapping technique is implemented to replace asymptotic analysis. The random intercepts model is fitted using a maximum likelihood estimator with adaptive Gauss-Hermite and Laplace quadrature approximations of the likelihood function. The fixed effects model is fitted through a profiling approach, which is necessary when the number of clusters is large. In a simulation study, the two approaches are compared. The fixed effects model has severe bias when the mixed effects variance is positive and the number of clusters is large.     

Enhanced chemosensing of ammonia based on the novel molecular semiconductor-doped insulator (MSDI) heterojunctions

A series of new molecular semiconductor-doped insulator (MSDI) heterojunctions as conductimetric transducers to NH₃ sensing were fabricated based on a novel semiconducting molecular material, an amphiphilic tris(phthalocyaninato) rare earth triple-decker complex, Eu₂[Pc(15C5)₄]₂[Pc(OC₁₀H₂₁)₈], quasi-Langmuir-Shäfer (QLS) film, as a top-layer, and vacuum-deposited and cast film of CuPc as well as copper tetra-tert-butyl phthalocyanine (CuTTBPc) QLS film as a sub-layer, named as MSDIs 1, 2 and 3, respectively. MSDIs 1-3 and respective sub-layers prepared from three different methods were characterized by X-ray diffraction, electronic absorption spectra and current-voltage (I-V) measurements. Depending on the sub-layer film-forming method used, α-phase CuPc film structure, β-phase CuPc crystallites and H-type aggregates of CuTTBPc have been obtained, respectively. An increasing sensitivity to NH₃ at varied concentrations in the range of 15-800 ppm, follows the order MSDI 2 < MSDI 3 < MSDI 1, revealing the effect of sub-layer film structures on sensing performance of the MSDIs. In particular, the time-dependent current plot of the MSDI 1, with α-phase CuPc film as a sub-layer, clearly shows an excellent separation of the different ammonia concentration levels and nearly complete reversibility and reproducibility even at room temperature, which is unique among the phthalocyanine-based ammonia sensors thus far reported in the literature. This provides a general method to improve sensor response of organic heterojunctions by controlling and tuning the film structure of sub-layer with appropriate fabrication techniques. On the other hand, the enhanced sensitivity, stability and reproducible response of the MSDI 1 heterostructure in comparison with the respective single-layer films have also been obtained. A judicious combination of materials and molecular architectures has led to enhanced sensing properties of the MSDI 1, in which control at the molecular level can be achieved.     

Geometric properties of partial least squares for process monitoring

Projection to latent structures or partial least squares (PLS) produces output-supervised decomposition on input X, while principal component analysis (PCA) produces unsupervised decomposition of input X. In this paper, the effect of output Y on the X-space decomposition in PLS is analyzed and geometric properties of the PLS structure are revealed. Several PLS algorithms are compared in a geometric way for the purpose of process monitoring. A numerical example and a case study are given to illustrate the analysis results.     

Feynman graph generation and calculations in the Hopf algebra of Feynman graphs

Two programs for the computation of perturbative expansions of quantum field theory amplitudes are provided. feyngen can be used to generate Feynman graphs for Yang–Mills, QED and φ^k${\phi }^k$ theories. Using dedicated graph theoretic tools feyngen can generate graphs of comparatively high loop orders. feyncop implements the Hopf algebra of those Feynman graphs which incorporates the renormalization procedure necessary to calculate finite results in perturbation theory of the underlying quantum field theory. feyngen is validated by comparison to explicit calculations of zero dimensional quantum field theories and feyncop is validated using a combinatorial identity on the Hopf algebra of graphs.     

A Maple package for improved global mapping forecast

We present a Maple implementation of the well known global approach to time series analysis and some further developments designed to improve the computational efficiency of the forecasting capabilities of the approach. This global approach can be summarized as being a reconstruction of the phase space, based on a time ordered series of data obtained from the system. After that, using the reconstructed vectors, a portion of this space is used to produce a mapping, a polynomial fitting, through a minimization procedure, that represents the system and can be employed to forecast further entries for the series. In the present implementation, we introduce a set of commands, tools, in order to perform all these tasks. For example, the command VecTS deals mainly with the reconstruction of the vector in the phase space. The command GfiTS deals with producing the minimization and the fitting. ForecasTS uses all these and produces the prediction of the next entries. For the non-standard algorithms, we here present two commands: IforecasTS and NiforecasTS that, respectively deal with the one-step and the N$N$-step forecasting. Finally, we introduce two further tools to aid the forecasting. The commands GfiTS and AnalysTS, basically, perform an analysis of the behavior of each portion of a series regarding the settings used on the commands just mentioned above.     

Novel carbazole/anthracene hybrids for efficient blue organic light-emitting diodes

Two novel carbazole/anthracene hybrided molecules, namely 2-(anthracen-9-yl)-9-ethyl-9H-carbazole (AnCz) and 2,7-di(anthracen-9-yl)-9-ethyl-9H-carbazole (2AnCz), were designed and synthesized via palladium catalyzed coupling reaction. The anthracene was attached either at the 2-site (AnCz) or at both 2,7-sites (2AnCz) of the central carbazole core to tune the conjugation state and the optoelectronic properties of the resultant molecules. Both of them show good solubility in common organic solvents. They also possess relatively high HOMO levels (−5.39 eV, −5.40 eV) that would facilitate efficient hole injection and be favorable for high power efficiencies when used in organic light-emitting devices (OLEDs). AnCz and 2AnCz were used as non-doped emitter to fabricate OLEDs by vacuum evaporation. Good performance was achieved with maximum luminance efficiency of 2.61 cd A⁻¹ and CIE coordinates of (0.15, 0.12) for AnCz, and 9.52 cd A⁻¹ and (0.22, 0.37) for 2AnCz.     

Deadline-sensitive workflow orchestration without explicit resource control

Deadline-sensitive workflows require careful coordination of user constraints with resource availability. Current distributed resource access models provide varying degrees of resource control: from limited or none in grid batch systems to explicit in cloud systems. Additionally applications experience variability due to competing user loads, performance variations, failures, etc. These variations impact the quality of service (QoS) that goes unaccounted for in planning strategies. In this paper we propose Workflow ORchestrator for Distributed Systems (WORDS) architecture based on a least common denominator resource model that abstracts the differences and captures the QoS properties provided by grid and cloud systems. We investigate algorithms for effective orchestration (i.e., resource procurement and task mapping) for deadline-sensitive workflows atop the resource abstraction provided in WORDS. Our evaluation compares orchestration methodologies over TeraGrid and Amazon EC2 systems. Experimental results show that WORDS enables effective orchestration possible at reasonable costs on batch queue grid and cloud systems with or without explicit resource control.     

Performance evaluation for a transportation system in stochastic case

In a single-commodity multistate flow network, the arc capacity is stochastic and thus the system capacity (i.e. the maximum flow from the source to the sink) is not a fixed number. This paper constructs a multicommodity multistate flow network with weighted capacity allocation to model a transportation system. Each arc with cost attribute has several possible capacities. The capacity weight, the consumed amount of arc capacity by per commodity, varies with the arcs and types of commodity. We define the system capacity as a demand vector d if the system fulfills at most d. The addressed problem in this work is to measure the service quality of a transportation system. We propose a performance index, the probability that the upper bound of the system capacity equals a demand vector d subject to the budget constraint. A simple algorithm based on minimal cuts is presented to generate all (d,B)-MC that are the maximal capacity vectors meeting exactly the demand d under the budget B. The proposed performance index can be subsequently evaluated in terms of such (d,B)-MC.     

Geometry-based semantic ID for persistent and interoperable reference in feature-based parametric modeling

In current feature-based parametric design systems, the reusability principle is not fully supported as it was expected. Unpredictability and ambiguity of models often happen during design modification within one system as well as among different systems. This reference deficiency significantly reduces the power of feature-based parametric modeling, where geometry re-evaluation generates unexpected shapes. In this paper, a sufficient condition of B-Rep variance based on geometry continuity in parametric complex Euclidean (P^pC³) space is proposed. Shape and relation parameters are differentiated in P^pC³, thus parametric family can be defined. A semantic id scheme based on continuity of geometry is developed to solve the problem of naming persistency and to improve interoperability of CAD feature modeling. Hierarchical namespaces localize entity creation and identification. All geometric and topological entities are referred uniformly based on surface ids, and topology semantics is retained in id itself.     

Salicylaldehyde based colorimetric and “turn on” fluorescent sensors for fluoride anion sensing employing hydrogen bonding

Two salicylaldehyde based colorimetric and fluorescent chemosensors 1 and 2 were developed. Both receptors 1 and 2 showed unique selectivity for the fluoride anions over other anions in DMSO solution. [TBA] OH and ¹H NMR titration experiments revealed that the F⁻-induced colorimetric and “turn on” fluorescence response were driven by hydrogen bonding interaction between the OH protons and F⁻.